CN110895012A - Air conditioner control method and device, storage medium and air conditioner - Google Patents
Air conditioner control method and device, storage medium and air conditioner Download PDFInfo
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- 230000008569 process Effects 0.000 claims description 15
- 238000004378 air conditioning Methods 0.000 claims description 10
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
- F24F11/72—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
- F24F11/72—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure
- F24F11/79—Control systems characterised by their outputs; Constructional details thereof for controlling the supply of treated air, e.g. its pressure for controlling the direction of the supplied air
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
- F24F11/80—Control systems characterised by their outputs; Constructional details thereof for controlling the temperature of the supplied air
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/88—Electrical aspects, e.g. circuits
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/10—Temperature
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/20—Humidity
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Abstract
The invention provides an air conditioner control method, an air conditioner control device, a storage medium and an air conditioner, wherein the method comprises the following steps: acquiring a current first environment parameter and a first position of a user; acquiring a pre-established neural network model for determining set operation parameters of the air conditioner; inputting the acquired first environmental parameter and the first position into the neural network model, and outputting a first set operation parameter; and controlling the operation of the air conditioner according to the output first set operation parameter. The scheme provided by the invention can quickly respond when the outdoor temperature, humidity or user position changes, and ensures the comfort of the user.
Description
Technical Field
The invention relates to the field of control, in particular to an air conditioner control method and device, a storage medium and an air conditioner.
Background
With the development of intelligent algorithms, household air conditioners are gradually using the intelligent algorithms to control air conditioners. However, in the prior art, although various intelligent algorithms are used for intelligently controlling the air conditioner to improve the comfort of the human body, the set temperature of the air conditioner is only adjusted from a macroscopic angle, and the air volume and the air outlet angle of the air conditioner are not accurately controlled according to the actual comfortable condition of the human body or the requirement of the human body.
Disclosure of Invention
The main purpose of the present invention is to overcome the above-mentioned drawbacks of the prior art, and to provide an air conditioner control method, device, storage medium and air conditioner, so as to solve the problem that the air volume and the air outlet angle of the air conditioner are not accurately controlled according to the actual human comfort or human needs in the prior art.
One aspect of the present invention provides an air conditioner control method, including: acquiring a current first environment parameter and a first position of a user; acquiring a pre-established neural network model for determining set operation parameters of the air conditioner; inputting the acquired first environmental parameter and the first position into the neural network model, and outputting a first set operation parameter; and controlling the operation of the air conditioner according to the output first set operation parameter.
Optionally, the pre-establishing a neural network model for determining the set operating parameters of the air conditioner includes: monitoring a second environmental parameter, a second position of a user and a PMV value at the second position in the running process of the air conditioner; adjusting the set operation parameters of the air conditioner according to the second position and the PMV value until the PMV value meets the preset PMV value requirement; recording the second environment parameter, the second position and a second set operation parameter of the air conditioner when the PMV value meets a preset PMV value requirement; and training a neural network model based on the second environment parameter, the second position and the second set operation parameter, and establishing the neural network model for determining the set operation parameter of the air conditioner.
Optionally, performing neural network model training based on a second environment parameter, the second location, and the second set operating parameter, and establishing a neural network model for determining the set operating parameter of the air conditioner includes: and taking the second environment parameter and the second position as input quantities, and taking the second set operation parameter as an output quantity to carry out neural network model training so as to establish the neural network model for determining the set operation parameter of the air conditioner.
Optionally, the pre-establishing a neural network model for determining the set operating parameters of the air conditioner further includes: when the air conditioner is started, acquiring first parameter setting data of the air conditioner stored by a cloud data platform and/or second parameter setting data of the air conditioner stored locally; setting initial set operation parameters of the air conditioner according to the first parameter setting data and/or the second parameter setting data based on initial environment parameters during starting; and controlling the air conditioner to operate according to the set initial set operation parameters.
Optionally, the setting the operation parameter includes: setting temperature, air quantity and/or air outlet angle of the upper air outlet and the lower air outlet; and/or, acquiring the first position of the user, including: the first position where the user is currently located is detected through the infrared sensor.
Optionally, the method further comprises: receiving a parameter adjusting instruction for adjusting the set operation parameters of the air conditioner; recording a third environment parameter and a third position of the user when the parameter adjusting instruction is received; recording a third set operation parameter after the set operation parameter of the air conditioner is adjusted according to the parameter adjustment instruction; and updating the neural network model by taking the third environmental parameter and the third position as input quantities and taking the third set operation parameter as an output quantity.
Another aspect of the present invention provides an air conditioning control apparatus, including: the first acquisition unit is used for acquiring a current first environment parameter and a first position where a user is located; the second acquisition unit is used for acquiring a pre-established neural network model for determining the set operation parameters of the air conditioner; the parameter output unit is used for inputting the acquired first environment parameter and the first position into the neural network model and outputting a first set operation parameter; and the control unit is used for controlling the operation of the air conditioner according to the output first set operation parameter.
Optionally, the method further comprises: a model establishing unit for establishing in advance a neural network model for determining set operation parameters of the air conditioner, including: monitoring a second environmental parameter, a second position of a user and a PMV value at the second position in the running process of the air conditioner; adjusting the set operation parameters of the air conditioner according to the second position and the PMV value until the PMV value meets the preset PMV value requirement; recording the second environment parameter, the second position and a second set operation parameter of the air conditioner when the PMV value meets a preset PMV value requirement; and training a neural network model based on the second environment parameter, the second position and the second set operation parameter, and establishing the neural network model for determining the set operation parameter of the air conditioner.
Optionally, the model establishing unit performs neural network model training based on a second environment parameter, the second location, and the second set operating parameter, and establishes a neural network model for determining the set operating parameter of the air conditioner, including: and taking the second environment parameter and the second position as input quantities, and taking the second set operation parameter as an output quantity to carry out neural network model training so as to establish the neural network model for determining the set operation parameter of the air conditioner.
Optionally, the model building unit is configured to pre-build a neural network model for determining the set operating parameters of the air conditioner, and further includes: when the air conditioner is started, acquiring first parameter setting data of the air conditioner stored by a cloud data platform and/or second parameter setting data of the air conditioner stored locally; setting initial set operation parameters of the air conditioner according to the first parameter setting data and/or the second parameter setting data based on initial environment parameters during starting; and controlling the air conditioner to operate according to the set initial set operation parameters.
Optionally, the setting the operation parameter includes: setting temperature, air quantity and/or air outlet angle of the upper air outlet and the lower air outlet; and/or, acquiring the first position of the user, including: the first position where the user is currently located is detected through the infrared sensor.
Optionally, the method further comprises: the receiving unit is used for receiving a parameter adjusting instruction for adjusting the set operation parameters of the air conditioner; the recording unit is used for recording a third environment parameter and a third position where the user is located when the parameter adjusting instruction is received and a third set operation parameter after the set operation parameter of the air conditioner is adjusted according to the parameter adjusting instruction; and the updating unit is used for updating the neural network model by taking the third environmental parameter and the third position as input quantities and taking the third set operation parameter as an output quantity.
A further aspect of the invention provides a storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of any of the methods described above.
Yet another aspect of the present invention provides an air conditioner comprising a processor, a memory, and a computer program stored on the memory and operable on the processor, wherein the processor implements the steps of any of the methods described above when executing the program.
In another aspect, the invention provides an air conditioner, which comprises the air conditioner control device.
According to the technical scheme of the invention, the neural network model training is carried out by utilizing the neural network algorithm based on the environmental parameters, the human body position and the set operation parameters when the PMV value meets the preset PMV value requirement, the response can be quickly made when the outdoor temperature, the humidity or the user position changes, the set temperature and the air output quantity and the air output angle of the upper air outlet and the lower air outlet are adjusted, and the comfort of the user is ensured. In addition, the invention can adjust the neural network model used in the control process according to the use condition of the air conditioner by the user, so that the neural network model can be controlled individually according to the habit of the user.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic diagram of an embodiment of an air conditioner control method according to the present invention;
FIG. 2 is a schematic flow chart diagram illustrating one embodiment of a neural network model for pre-establishing set operating parameters of the air conditioner in accordance with the present invention;
FIG. 3 is a schematic diagram of an air conditioner control method according to another embodiment of the present invention;
FIG. 4 is a schematic diagram of an embodiment of a method for controlling an air conditioner according to the present invention;
FIG. 5 is a schematic structural diagram of an embodiment of an air conditioning control apparatus provided by the present invention;
fig. 6 is a schematic structural diagram of another embodiment of an air conditioning control device provided by the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the specific embodiments of the present invention and the accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The invention provides an air conditioner control method. The air conditioner control method can be particularly used for an air conditioner with an upper air outlet and a lower air outlet. The air quantity and the angle of the upper air outlet and the lower air outlet of the air conditioner can be independently controlled.
Fig. 1 is a schematic method diagram of an embodiment of an air conditioner control method provided by the present invention.
As shown in fig. 1, according to an embodiment of the present invention, the air conditioner control method includes at least step S110, step S120, step S130, and step S140.
Step S110, obtain a current first environment parameter and a first location where the user is located.
The first environmental parameter may specifically comprise an outdoor ambient temperature and/or an outdoor ambient humidity. The first position of the current user can be detected by an infrared sensor.
And step S120, acquiring a pre-established neural network model for determining the set operation parameters of the air conditioner.
Specifically, the pre-establishing of the neural network model for determining the set operation parameters of the air conditioner may specifically include the following steps S1 to S5.
And step S1, setting initial setting operation parameters according to the initial environment parameters when the air conditioner is started, and controlling the air conditioner to operate according to the initial setting operation parameters.
Specifically, when the air conditioner is started, first parameter setting data of the air conditioner, which is stored by a cloud data platform, and/or second parameter setting data of the air conditioner, which is locally stored, are obtained; setting initial set operation parameters of the air conditioner according to the first parameter setting data and/or the second parameter setting data based on initial environment parameters during starting; and controlling the air conditioner to operate according to the set initial set operation parameters.
The first parameter setting data can be parameter setting data of a plurality of users stored by a cloud data platform, and the second parameter setting data can be parameter setting data of the air conditioner, which are locally stored by the users. For example, if the outdoor temperature is 33 degrees, the setting temperature preferred by most users in the cloud data is 25 degrees, and the air volume is medium-high; if the outdoor temperature is 28 ℃, the favorite temperature of most users in the cloud data is set to be 27 ℃, and the air volume is low or medium; when the outdoor temperature is 33 degrees, the temperature is manually set to 24 degrees and the air volume is high, when the outdoor temperature is 28 degrees, the temperature is manually set to 25 degrees and the air volume is medium-high, when the outdoor temperature is 28 degrees, the temperature of the air conditioner is set to 26 degrees and the air volume is medium-high, and the air conditioner is controlled to operate according to the set temperature of 26 degrees and the air volume is medium-high.
And step S2, monitoring a second environmental parameter, a second position where the user is located and a PMV value at the second position during the operation process of the air conditioner.
Specifically, the PMV value at the second location and the second location where the user is located may be detected by the infrared sensor. The second environmental parameter may specifically comprise an outdoor ambient temperature and/or an outdoor ambient humidity. The PMV value can be calculated according to indoor temperature, humidity, wind speed and radiation temperature, wherein the wind speed is calculated according to a second position where a user is located and the air volume of the air outlet, the radiation temperature is in direct proportion to the indoor temperature, the indoor temperature and the humidity can be detected through a temperature and humidity sensor carried by the air conditioner, the calculation of the PMV value is the prior art, and therefore the calculation is omitted for further description.
And step S3, adjusting the set operation parameters of the air conditioner according to the second position and the PMV value until the PMV value reaches the preset PMV value requirement.
Specifically, the air volume and/or the air outlet angle of the upper air outlet and the lower air outlet of the air conditioner are adjusted according to the second position and the PMV value, so that the PMV value around the position where the user is located reaches the preset PMV value requirement. For example, the PMV value is related to the wind speed, so that the wind output (e.g. the wind output of the upper and lower outlets) and the wind output angle can be controlled according to the second position where the user is located, so that the wind speed around the user is suitable.
And step S4, recording the second environmental parameter, the second position and a second set operation parameter of the air conditioner when the PMV value reaches a preset PMV value requirement.
And recording the second environment parameter, the second position and a second set operation parameter of the air conditioner when the PMV value reaches a preset PMV value requirement, wherein the second set operation parameter comprises a set temperature, and the air volume and/or the air outlet angle of the upper air outlet and the lower air outlet of the air conditioner.
And step S5, training a neural network model based on the second environment parameter, the second position and the second set operation parameter, and establishing the neural network model for determining the set operation parameter of the air conditioner.
Specifically, the second environmental parameter and the second position are used as input quantities, and the second set operation parameter is used as an output quantity to perform neural network model training, so as to establish the neural network model for determining the set operation parameter of the air conditioner. The neural network model may specifically include a BP neural network model or a REF neural network model.
The neural network model is trained on the basis of the set operating parameters when the environmental parameters, the human body position and the PMV value meet the preset PMV value requirement, and can quickly respond when the environmental parameters (such as outdoor temperature and humidity) or the user position change, so that the comfort of the user is ensured.
For example, fig. 2 is a schematic flow chart of an embodiment of the present invention for pre-establishing a neural network model for determining set operating parameters of the air conditioner. Referring to fig. 2, the initial BP neural network of the air conditioner may be trained and determined by cloud data, and the input is a human body position, an outdoor temperature, humidity, and the like, and the output is a set temperature of the air conditioner, and an air volume and an air outlet angle of an upper air outlet and a lower air outlet. The BP network can continuously carry out adaptive learning according to the use condition (local data) of a user in the use process of the user, and finally, the network with user personalized setting is realized, so that the air conditioner can carry out intelligent control according to the preference of the user.
Step S130, inputting the acquired first environmental parameter and the first position into the neural network model, and outputting a first set operating parameter.
The input quantity of the neural network model is an environment parameter and the position of a user, and the output quantity is a set operation parameter, so that the first environment parameter and the first position are input into the neural network model, and the current first set operation parameter of the air conditioner can be output. The first set operation parameters comprise set temperature of the air conditioner, air quantity and/or air outlet angle of the upper air outlet and the lower air outlet.
And step S140, controlling the operation of the air conditioner according to the output first set operation parameter.
That is, the air conditioner is controlled to operate according to the first set operating parameter.
Although the air conditioner can be intelligently controlled according to the PMV value in the prior art, and the set temperature and the air outlet state can be adjusted according to the actual situation when the PMV value does not meet the requirement, the temperature control system is a system with time ductility, and the air conditioner can be controlled after the PMV value of a human body is monitored to change, so that the requirement of the human body for comfort needs to be met for a period of time. According to the embodiment of the invention, the neural network model is used for outputting the corresponding set operation parameters, so that the response can be quickly made when the outdoor temperature, humidity or user position changes, and the comfort of the user is ensured.
Fig. 3 is a method schematic diagram of another embodiment of the air conditioner control method provided by the invention. As shown in fig. 3, according to another embodiment of the present invention, the air conditioner control method further includes step S150, step S160, step S170, and step S180.
And step S150, receiving a parameter adjusting instruction for adjusting the set operation parameters of the air conditioner.
Step S160, recording a third environmental parameter and a third location of the user when the parameter adjustment instruction is received.
And step S170, recording a third set operation parameter after the set operation parameter of the air conditioner is adjusted according to the parameter adjusting instruction.
And step S180, updating the neural network model by taking the third environmental parameter and the third position as input quantities and taking the third set operation parameter as an output quantity.
Specifically, when the operation of the air conditioner is controlled according to the output first set operation parameter, the user may adjust the set operation parameter of the air conditioner according to his/her own comfort, for example, if the user sends a parameter adjustment instruction for adjusting the set operation parameter of the air conditioner, for example, adjustment of the set temperature, adjustment of the air volume of the upper and lower outlets, and/or adjustment of the air outlet angle of the upper and lower outlets. Recording the environmental parameters and the position of the user when the parameter adjusting instruction of the user is received, and recording the set operation parameters after the set operation parameters of the air conditioner are adjusted according to the parameter adjusting instruction of the user, so that the recorded environmental parameters and the position of the user are used as input quantities, and the adjusted set operation parameters are used as output quantities to update and adjust the neural network model.
According to the embodiment of the invention, the neural network model used in the control process can be adjusted according to the use habits of the user, so that the neural network model can be controlled in a personalized manner according to the use habits of the user. The method realizes continuous adaptive learning according to the use condition of the user in the use process of the air conditioner by the user.
For clearly explaining the technical solution of the present invention, the following describes an execution flow of the air conditioner control method provided by the present invention with a specific embodiment.
Fig. 4 is a schematic method diagram of an embodiment of an air conditioner control method according to the present invention. As shown in fig. 4, after the air conditioner is started, the air conditioner determines an initial temperature (initial set temperature), an initial air volume and an air outlet angle according to cloud data and local data, monitors a human body position and a PMV value through an infrared sensor, performs targeted adjustment on the air volume and the air outlet angle according to whether the PMV value reaches the standard or not until the PMV value requirement of a user is met, and records data at the moment for neural network learning. If the user sends an instruction of switching to manual operation, the air conditioner is switched to manual operation until the user switches to an automatic control instruction; if the user sends other instructions except for manual operation, such as temperature adjustment, air output adjustment and the like, the air conditioner can update the adjusted parameters to local data while adjusting in real time according to the instructions. If environmental factors are changed, if the outdoor temperature and humidity are changed, the air conditioner can adjust the air output and the air output angle in a targeted mode, the comfort of the air conditioner is guaranteed, data at the moment are recorded, and neural network model training is carried out, so that the control speed when similar conditions are monitored next time is increased.
The invention provides an air conditioner control device. The air conditioner control method can be particularly used for an air conditioner with an upper air outlet and a lower air outlet. The air quantity and the angle of the upper air outlet and the lower air outlet of the air conditioner can be independently controlled.
Fig. 5 is a schematic structural diagram of an embodiment of an air conditioning control device provided in the present invention. As shown in fig. 5, the air conditioning control apparatus 100 includes a first acquisition unit 110, a second acquisition unit 120, a parameter output unit 130, and a control unit 140.
The first obtaining unit 110 is configured to obtain a current first environment parameter and a first location where a user is located. The first environmental parameter may specifically comprise an outdoor ambient temperature and/or an outdoor ambient humidity. The first obtaining unit 110 may detect a first location where the current user is located through an infrared sensor.
The second obtaining unit 120 is configured to obtain a pre-established neural network model for determining set operating parameters of the air conditioner.
Specifically, the apparatus 100 may further include a model building unit (not shown) for building a neural network model for determining set operation parameters of the air conditioner in advance.
The pre-establishing of the neural network model for determining the set operation parameters of the air conditioner by the model establishing unit may specifically include the following steps S1 to S5.
And step S1, setting initial setting operation parameters according to the initial environment parameters when the air conditioner is started, and controlling the air conditioner to operate according to the initial setting operation parameters.
Specifically, when the air conditioner is started, first parameter setting data of the air conditioner, which is stored by a cloud data platform, and/or second parameter setting data of the air conditioner, which is locally stored, are obtained; setting initial set operation parameters of the air conditioner according to the first parameter setting data and/or the second parameter setting data based on initial environment parameters during starting; and controlling the air conditioner to operate according to the set initial set operation parameters.
The first parameter setting data can be parameter setting data of a plurality of users stored by a cloud data platform, and the second parameter setting data can be parameter setting data of the air conditioner, which are locally stored by the users. For example, if the outdoor temperature is 33 degrees, the setting temperature preferred by most users in the cloud data is 25 degrees, and the air volume is medium-high; if the outdoor temperature is 28 ℃, the favorite temperature of most users in the cloud data is set to be 27 ℃, and the air volume is low or medium; when the outdoor temperature is 33 degrees, the temperature is manually set to 24 degrees and the air volume is high, when the outdoor temperature is 28 degrees, the temperature is manually set to 25 degrees and the air volume is medium-high, when the outdoor temperature is 28 degrees, the temperature of the air conditioner is set to 26 degrees and the air volume is medium-high, and the air conditioner is controlled to operate according to the set temperature of 26 degrees and the air volume is medium-high.
And step S2, monitoring a second environmental parameter, a second position where the user is located and a PMV value at the second position during the operation process of the air conditioner.
Specifically, the PMV value at the second location and the second location where the user is located may be detected by the infrared sensor. The second environmental parameter may specifically comprise an outdoor ambient temperature and/or an outdoor ambient humidity. The PMV value can be calculated according to indoor temperature, humidity, wind speed and radiation temperature, wherein the wind speed is calculated according to a second position where a user is located and the air volume of the air outlet, the radiation temperature is in direct proportion to the indoor temperature, the indoor temperature and the humidity can be detected through a temperature and humidity sensor carried by the air conditioner, the calculation of the PMV value is the prior art, and therefore the calculation is omitted for further description.
And step S3, adjusting the set operation parameters of the air conditioner according to the second position and the PMV value until the PMV value reaches the preset PMV value requirement.
Specifically, the air volume and/or the air outlet angle of the upper air outlet and the lower air outlet of the air conditioner are adjusted according to the second position and the PMV value, so that the PMV value around the position where the user is located reaches the preset PMV value requirement. For example, the PMV value is related to the wind speed, so that the wind output (e.g. the wind output of the upper and lower outlets) and the wind output angle can be controlled according to the second position where the user is located, so that the wind speed around the user is suitable.
And step S4, recording the second environmental parameter, the second position and a second set operation parameter of the air conditioner when the PMV value reaches a preset PMV value requirement.
And recording the second environment parameter, the second position and a second set operation parameter of the air conditioner when the PMV value reaches a preset PMV value requirement, wherein the second set operation parameter comprises a set temperature, and the air volume and/or the air outlet angle of the upper air outlet and the lower air outlet of the air conditioner.
And step S5, training a neural network model based on the second environment parameter, the second position and the second set operation parameter, and establishing the neural network model for determining the set operation parameter of the air conditioner.
Specifically, the second environmental parameter and the second position are used as input quantities, and the second set operation parameter is used as an output quantity to perform neural network model training, so as to establish the neural network model for determining the set operation parameter of the air conditioner. The neural network model may be specifically a BP neural network model or a REF neural network model.
For example, fig. 2 is a schematic flow chart of an embodiment of the present invention for pre-establishing a neural network model for determining set operating parameters of the air conditioner. Referring to fig. 2, the initial BP neural network of the air conditioner may be trained and determined by cloud data, and the input is a human body position, an outdoor temperature, humidity, and the like, and the output is a set temperature of the air conditioner, and an air volume and an air outlet angle of an upper air outlet and a lower air outlet. The BP network can continuously carry out adaptive learning according to the use condition (local data) of a user in the use process of the user, and finally, the network with user personalized setting is realized, so that the air conditioner can carry out intelligent control according to the preference of the user.
The parameter output unit 130 is configured to input the acquired first environmental parameter and the first location into the neural network model, and output a first set operating parameter.
The input quantity of the neural network model is an environment parameter and the position of a user, and the output quantity is a set operation parameter, so that the first environment parameter and the first position are input into the neural network model, and the current first set operation parameter of the air conditioner can be output. The first set operation parameters comprise set temperature of the air conditioner, air quantity and/or air outlet angle of the upper air outlet and the lower air outlet.
The control unit 140 is configured to control the operation of the air conditioner according to the output first set operation parameter. That is, the control unit 140 controls the air conditioner to operate according to the first set operating parameter.
The invention provides an air conditioner control device. The air conditioner control device can be particularly used for an air conditioner with an upper air outlet and a lower air outlet. The air quantity and the angle of the upper air outlet and the lower air outlet of the air conditioner can be independently controlled.
Fig. 6 is a schematic structural diagram of another embodiment of an air conditioning control device provided by the invention. As shown in fig. 6, based on the above-described embodiment, the air conditioning control apparatus 100 further includes a receiving unit 150, a recording unit 160, and an updating unit 170.
The receiving unit 150 is configured to receive a parameter adjustment instruction for adjusting a set operation parameter of the air conditioner. The recording unit 160 is configured to record a third environmental parameter and a third location where the user is located when the receiving unit 150 receives the parameter adjustment instruction, and a third set operation parameter obtained by adjusting the set operation parameter of the air conditioner according to the parameter adjustment instruction. The updating unit 170 is configured to update the neural network model by using the third environmental parameter and the third position as input quantities and using the third set operating parameter as an output quantity.
Specifically, when the operation of the air conditioner is controlled according to the output first set operation parameter, the user may adjust the set operation parameter of the air conditioner according to his/her own comfort, for example, if the user sends a parameter adjustment instruction for adjusting the set operation parameter of the air conditioner, for example, adjustment of the set temperature, adjustment of the air volume of the upper and lower outlets, and/or adjustment of the air outlet angle of the upper and lower outlets. The recording unit 160 records the environmental parameters and the location of the user when receiving the parameter adjustment instruction of the user, and records the set operation parameters after adjusting the set operation parameters of the air conditioner according to the parameter adjustment instruction of the user, so that the updating unit 170 uses the recorded environmental parameters and the location of the user as input quantities, and uses the adjusted set operation parameters as output quantities to update the neural network model. The method realizes continuous adaptive learning according to the use condition of the user in the use process of the air conditioner by the user.
The present invention also provides a storage medium corresponding to the air conditioning control method, having a computer program stored thereon, which when executed by a processor, performs the steps of any of the aforementioned methods.
The invention also provides an air conditioner corresponding to the air conditioner control method, which comprises a processor, a memory and a computer program which is stored on the memory and can run on the processor, wherein the processor realizes the steps of any one of the methods when executing the program.
The invention also provides an air conditioner corresponding to the air conditioner control device, which comprises the air conditioner control device.
Therefore, according to the scheme provided by the invention, the neural network model training is carried out by utilizing the neural network algorithm based on the set operation parameters when the environmental parameters, the human body position and the PMV value meet the preset PMV value requirement, the response can be quickly made when the outdoor temperature, the humidity or the user position changes, the set temperature and the air output quantity and the air output angle of the upper air outlet and the lower air outlet are adjusted, and the comfort of the user is ensured. In addition, the invention can adjust the neural network model used in the control process according to the use condition of the air conditioner by the user, so that the neural network model can be controlled individually according to the habit of the user.
The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Other examples and implementations are within the scope and spirit of the invention and the following claims. For example, due to the nature of software, the functions described above may be implemented using software executed by a processor, hardware, firmware, hardwired, or a combination of any of these. In addition, each functional unit may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and the parts serving as the control device may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The above description is only an example of the present invention, and is not intended to limit the present invention, and it is obvious to those skilled in the art that various modifications and variations can be made in the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (14)
1. An air conditioner control method, comprising:
acquiring a current first environment parameter and a first position of a user;
acquiring a pre-established neural network model for determining set operation parameters of the air conditioner;
inputting the acquired first environmental parameter and the first position into the neural network model, and outputting a first set operation parameter;
and controlling the operation of the air conditioner according to the output first set operation parameter.
2. The method of claim 1, wherein pre-establishing a neural network model for determining set operating parameters of the air conditioner comprises:
monitoring a second environment parameter of the environment, a second position of a user and a PMV value at the second position in the running process of the air conditioner;
adjusting the set operation parameters of the air conditioner according to the second position and the PMV value until the PMV value meets the preset PMV value requirement;
recording the second environment parameter, the second position and a second set operation parameter of the air conditioner when the PMV value meets a preset PMV value requirement;
and training a neural network model based on the second environment parameter, the second position and the second set operation parameter, and establishing the neural network model for determining the set operation parameter of the air conditioner.
3. The method of claim 2, wherein performing neural network model training based on a second environmental parameter, the second location, and the second set operating parameter, building a neural network model for determining the set operating parameter of the air conditioner comprises:
and taking the second environment parameter and the second position as input quantities, and taking the second set operation parameter as an output quantity to carry out neural network model training so as to establish the neural network model for determining the set operation parameter of the air conditioner.
4. The method of claim 2 or 3, wherein a neural network model for determining the set operation parameters of the air conditioner is previously established, further comprising:
when the air conditioner is started, acquiring first parameter setting data of the air conditioner stored by a cloud data platform and/or second parameter setting data of the air conditioner stored locally;
setting initial set operation parameters of the air conditioner according to the first parameter setting data and/or the second parameter setting data based on initial environment parameters during starting;
and controlling the air conditioner to operate according to the set initial set operation parameters.
5. The method according to any one of claims 1 to 4,
the setting of the operating parameters comprises: setting temperature, air quantity and/or air outlet angle of the upper air outlet and the lower air outlet;
and/or the presence of a gas in the gas,
acquiring a first position of a user, comprising: the first position where the user is currently located is detected through the infrared sensor.
6. The method of any one of claims 1-5, further comprising:
receiving a parameter adjusting instruction for adjusting the set operation parameters of the air conditioner;
recording a third environment parameter and a third position of the user when the parameter adjusting instruction is received;
recording a third set operation parameter after the set operation parameter of the air conditioner is adjusted according to the parameter adjustment instruction;
and updating the neural network model by taking the third environmental parameter and the third position as input quantities and taking the third set operation parameter as an output quantity.
7. An air conditioning control device, characterized by comprising:
the first acquisition unit is used for acquiring a current first environment parameter and a first position where a user is located;
the second acquisition unit is used for acquiring a pre-established neural network model for determining the set operation parameters of the air conditioner;
the parameter output unit is used for inputting the acquired first environment parameter and the first position into the neural network model and outputting a first set operation parameter;
and the control unit is used for controlling the operation of the air conditioner according to the output first set operation parameter.
8. The apparatus of claim 7, further comprising: a model establishing unit for establishing in advance a neural network model for determining set operation parameters of the air conditioner, including:
monitoring a second environmental parameter, a second position of a user and a PMV value at the second position in the running process of the air conditioner;
adjusting the set operation parameters of the air conditioner according to the second position and the PMV value until the PMV value meets the preset PMV value requirement;
recording the second environment parameter, the second position and a second set operation parameter of the air conditioner when the PMV value meets a preset PMV value requirement;
and training a neural network model based on the second environment parameter, the second position and the second set operation parameter, and establishing the neural network model for determining the set operation parameter of the air conditioner.
9. The apparatus of claim 8, wherein the model building unit performs neural network model training based on a second environment parameter, the second location and the second set operation parameter, and builds a neural network model for determining the set operation parameter of the air conditioner, comprising:
and taking the second environment parameter and the second position as input quantities, and taking the second set operation parameter as an output quantity to carry out neural network model training so as to establish the neural network model for determining the set operation parameter of the air conditioner.
10. The apparatus of claim 8 or 9, wherein the model building unit pre-builds a neural network model for determining the set operation parameters of the air conditioner, further comprising:
when the air conditioner is started, acquiring first parameter setting data of the air conditioner stored by a cloud data platform and/or second parameter setting data of the air conditioner stored locally;
setting initial set operation parameters of the air conditioner according to the first parameter setting data and/or the second parameter setting data based on initial environment parameters during starting;
and controlling the air conditioner to operate according to the set initial set operation parameters.
11. The apparatus according to any one of claims 7 to 10,
the setting of the operating parameters comprises: setting temperature, air quantity and/or air outlet angle of the upper air outlet and the lower air outlet;
and/or the presence of a gas in the gas,
acquiring a first position of a user, comprising: the first position where the user is currently located is detected through the infrared sensor.
12. The apparatus of any one of claims 7-11, further comprising:
the receiving unit is used for receiving a parameter adjusting instruction for adjusting the set operation parameters of the air conditioner;
the recording unit is used for recording a third environment parameter and a third position where the user is located when the parameter adjusting instruction is received and a third set operation parameter after the set operation parameter of the air conditioner is adjusted according to the parameter adjusting instruction;
and the updating unit is used for updating the neural network model by taking the third environmental parameter and the third position as input quantities and taking the third set operation parameter as an output quantity.
13. A storage medium, having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
14. An air conditioner comprising a processor, a memory, and a computer program stored on the memory and operable on the processor, the processor implementing the steps of the method of any one of claims 1 to 6 when executing the program, or comprising the air conditioning control apparatus of any one of claims 7 to 12.
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